CN108256797B - Cargo transportation state detection method - Google Patents
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Abstract
A cargo transportation state detection method is characterized in that a basic circuit unit based on a three-axis acceleration sensor and an MCU microprocessor is adopted, the MCU continuously reads original XYZ values of the three-axis acceleration sensor at a frequency of 1KHz, the original XYZ values of the three-axis acceleration sensor are processed according to a corresponding algorithm, states of cargos in all time periods are output in real time, real-time qualitative analysis is realized on the basis of quantitative analysis of a cargo transportation state, and real-time positioning alarm can be realized by combining other communication modes and positioning modes, so that the method is favorable for immediately correcting transportation problems, and can also be used for post analysis or pursuing responsibility.
Description
Technical Field
The invention relates to the field of physics, in particular to a state detection technology of goods in a transportation process, and particularly relates to a goods transportation state detection method.
Background
During transportation, particularly loading and unloading, dangerous conditions often occur to cause damage to the goods, including: falling, bumping, tipping, jolting, etc. In the prior art, a multi-purpose three-axis acceleration sensor records extreme values in a period of XYZ three axes in the process of cargo transportation loading and unloading, different threshold values are set through different cargos or packages to judge that the cargos are possibly damaged, cargo labels based on physical characteristics can be used for judging afterwards in the market at present, but the prior art only carries out quantitative analysis and cannot carry out accurate qualitative analysis on whether the cargos are damaged.
Disclosure of Invention
The invention aims to solve the defects in the prior art, can realize real-time qualitative analysis of 7 dangers such as free fall, falling, collision, overturn, movement, jolt and the like, assists extreme values of three axes of XYZ, the height of the free fall and inclination angle values in the three directions of XYZ, can be used for field alarm, platform remote alarm or event analysis, provides a quantitative and qualitative solution for the cargo state, can help a cargo owner to improve a packaging scheme, and can also help a transportation enterprise to promote an operation process.
The main working principle is based on a basic circuit unit of a triaxial acceleration sensor and an MCU (micro controller unit), the MCU continuously reads original XYZ values of the triaxial acceleration sensor at the frequency of 1KHz, and then the original XYZ values are processed according to a corresponding algorithm and then the states of goods in various time periods are output in real time.
In order to achieve the purpose, the invention adopts the following technical scheme: a cargo transportation state detection method comprises the steps of fixedly connecting a three-axis acceleration sensor in a cargo or a cargo package and detecting an output signal of the three-axis acceleration sensor by using a microprocessor, wherein in the process, the microprocessor is used for continuously reading values of the three-axis acceleration sensor in the X-axis direction, the Y-axis direction and the Z-axis direction at the frequency of 1KHz, and then real-time algorithm processing is carried out.
In the real-time algorithm processing process, firstly, initializing system parameters, setting a static state direction DR as an X axis, assigning DR as 1, setting a free FALL height counter FALL value as 0, and setting a theoretical static wavelet counter SN value as 0; after the detection period starts, the extreme values Xmax, Ymax and Zmax of the three axes in the initialization period, the inclination angle extreme values AngleXmax, AngleYmax and AngleZmax of the three axes in the period and the free falling height counter FALLmax in the period are all assigned to be 0, and the qualitative analysis result SA in the period is assigned to be 0000000; continuously reading more than two groups of numerical values, comparing to obtain extreme values of three XYZ axes to form a sampling point S (X, Y, Z), and updating Xmax, Ymax and Zmax if the extreme values of the three axes are greater than Xmax, Ymax and Zmax; after a plurality of groups of sampling points are continuously obtained, every 5 continuous groups of sampling points are selected to form a wavelet W (S1, S2, S3, S4 and S5), so that a plurality of groups of wavelets W are formed, the state of the goods at the moment can be qualitatively judged by analyzing the three continuous groups of wavelets W, and the qualitative judgment method comprises the following steps: if the three-axis average values of 5 sampling points of a certain wavelet Wi are all smaller than 0.1, judging that the wavelet Wi is in a free-FALL state, assigning the state qualitative analysis result SAi of the wavelet Wi to be 1000000, adding 1 to the FALL value, updating the FALLmax if the FALL is larger than the FALLmax, giving the SA values after the SA and the SAi are subjected to logic AND operation, and finishing the qualitative analysis of the wavelet Wi; if the triaxial average values of 5 sampling points of a certain wavelet Wi are all larger than or equal to 0.1, the FALL is assigned with 0, and the next analysis is continued; if the previous wavelet Wi-1 of a certain wavelet Wi is qualitatively analyzed to be in a free falling body state and at least one of the three-axis average values of 5 sampling points of the wavelet Wi is more than 0.1, judging that the wavelet Wi is in a falling collision state, assigning the qualitative analysis result SAi of the state of the wavelet Wi to be 0100000, assigning the value obtained after the SA and the SAi are subjected to logic AND operation to the SA, and completing the qualitative analysis of the wavelet Wj; if the previous wavelet Wi-1 is qualitatively analyzed to be in a free falling body state and the condition that at least one of the three-axis average values of 5 sampling points of the wavelet Wi adjacent to the wavelet is greater than 0.1 does not hold, continuing the next analysis; if the triaxial extreme value differences of 5 sampling points of a certain wavelet Wi are all smaller than 0.15, judging the wavelet Wi to be in a theoretical static state, and adding 1 to the SN value; if the SN value is greater than 10 at the moment, if the axis DRi of the maximum value in the average values of the three axes of the 5 sampling points of the wavelet Wi and the DR are not the same axis and the difference distance between the value of the DRi and the value of the DR is greater than 0.3, judging that the wavelet Wi is in the overturn state, assigning the qualitative analysis result SAi of the state of the wavelet Wi to be 0001000, otherwise judging that the wavelet Wi is in the actual static state, assigning the qualitative analysis result SAi of the state of the wavelet Wi to be 0010000, assigning the value of the SA and the SAi after performing logic and operation to the SA, updating the static state direction DR to the direction pointed by the DRi, assigning the value of the DRi to the DR, and converting the arc value into an angle, comparing the arc value with the AngleXmax, AngleYmax and AngleZmax, and updating an extreme value; if the condition that the SN value is less than or equal to 10 or the triaxial extreme value differences of 5 sampling points of a certain wavelet Wi are less than 0.15 does not hold, continuing the next analysis; if the variance of three axes of 10 sampling points of a certain wavelet Wi and the next wavelet Wi +1 is larger than 0.3, judging Wi to be in an impact state, assigning 0000100 to the qualitative analysis result SAi of the state of the wavelet Wi, and assigning the value obtained after the SA and the SAi are subjected to logic AND operation to the SA; otherwise, continuing the next analysis; if the three-axis variances of 5 sampling points of a certain wavelet Wi are all smaller than 0.01, judging Wi to be in a moving state, assigning 0000010 to the wavelet Wi state qualitative analysis result SAi, and assigning the SA to a value obtained after the SA and the SAi are subjected to logic AND operation; otherwise, continuing the next analysis; directly judging Wi as a bumpy state, assigning 0000001 to the wavelet Wi state qualitative analysis result SAi, and assigning the SA with the value obtained after the SA and the SAi are subjected to logic AND operation; if the cycle time has not ended, continuing to analyze the subsequent wavelets, if the cycle time has ended, outputting the values of the extrema Xmax, Ymax, Zmax of the three axes, the extrema anguxexmax, AngleYmax, AngleZmax of the three axes, and the qualitative analysis result SA of the states in the cycle, and outputting the calculation result of 0.5 x 9.8 (FALLmax 0.025), which is the height of the free fall of the cargo in the cycle.
Further, the number of the sampling points S (X, Y, Z) required to be read continuously is 5 sets.
Compared with the prior art, the invention has positive and obvious effect, realizes real-time qualitative analysis on the basis of carrying out quantitative analysis on the cargo transportation state, can realize real-time positioning alarm by combining other communication modes and positioning modes, is favorable for immediately correcting transportation problems, and can also be used for post analysis or pursuing accountability.
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FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
Example (b):
as shown in fig. 1, a cargo transportation state detection method includes a three-axis acceleration sensor and an MCU microprocessor, and is characterized in that the three-axis acceleration sensor is disposed in a cargo package, and during a cargo transportation process, the MCU microprocessor continuously reads values of the three-axis acceleration sensor in X, Y, Z three-axis directions at a frequency of 1KHz, and then performs real-time arithmetic operation, wherein the processing steps are as follows: initializing system parameters: the direction DR of the system static state is an X axis, the value (DR) of the DR is assigned 1, the free FALL height counter FALL is assigned 0, and the theoretical static wavelet counter SN is assigned 0;
0. starting a cycle, initializing extreme values Xmax, Ymax and Zmax of three XYZ axes in the cycle, and inclination angle extreme values AngleXmax, AngleYmax and AngleZmax of the three axes in the cycle, and a free falling height counter FALLmax in the cycle, wherein the values are all assigned to 0, and the value of the state qualitative analysis SA in the cycle is assigned to '0000000' (the 1 st bit to the 7 th bit respectively represent a free falling body, a falling collision, a rest, a collision, a turnover, a movement and a bump, wherein the state is 1, and the state is not 0).
1. The data of a plurality of groups are continuously read, the extreme values of the three XYZ axes are obtained through numerical comparison, a sampling point S00(X, Y, Z) is formed, and the Xmax, Ymax and Zmax values are compared and updated with the extreme values of the three XYZ axes Xmax, Ymax and Zmax in the period.
2. The step 1 is repeated until 5 values of S01, S02, S03, S04 are successively obtained, and a wavelet W0 is composed of 5 values of S00, S01, S02, S03, S04 (S00, S01, S02, S03, S04).
3. Repeating the steps 1 and 2, obtaining W1(S10, S11, S12, S13 and S14) and W2(S20, S21, S22, S23 and S24) in succession, completing W3 and W4 … … by completing W2 wavelet assembly, and carrying out qualitative analysis on the state of Wi based on three wavelets of Wi-1, Wi and Wi +1 as follows:
3.1 if the average value | AVG (X, Y, Z) | of the three axes of XYZ of 5 sampling points of the Wi wavelet is less than 0.1, judging that the time slice where the Wi is located is a free-fall wavelet, assigning 1000000 to the wavelet state SAi, and finishing the qualitative analysis after the following analysis is finished; otherwise, assigning a value of 0 to a free FALL height counter FALL, and continuing the next analysis;
3.1.1 adding 1 to the free FALL height counter FALL, if FALL is greater than the free FALL height in the cycle FALLmax, then updating the value of FALLmax.
And assigning the values of the state qualitative analysis SA and the state qualitative analysis SAi after the AND operation in the period of 3.1.2 to the SA.
3.2 if the qualitative analysis state of Wi-1 is a free fall, and at least one of the average values | AVG (X, Y, Z) | of the three axes XYZ of the 5 sampling points of the Wi wavelet is greater than 0.1, judging that the time slice where the Wi is located is a drop-impact wavelet, assigning the value of the wavelet state SAi to 0100000, assigning the value of the sum of the state qualitative analysis SA and the SAi in the period to the SA, and then finishing the qualitative analysis; otherwise, continuing the next analysis;
3.3 if the extreme value differences Max (X, Y, Z) -Min (X, Y, Z) of the three XYZ axes of the 5 sampling points of the Wi wavelet are all smaller than 0.15, judging that the time slice where the Wi is located is the theoretical static wavelet, adding 1 to a theoretical static wavelet counter SN, and if not, assigning the value of the theoretical static wavelet counter SN to be 0 and continuing the next analysis. If the theoretical stationary wavelet counter SN exceeds 10, the following analysis is performed;
the axis DRi of the maximum value in the average | AVG (X, Y, Z) | of the three axes of 5 sampling points XYZ of the 3.3.1 Wi wavelet is not the same axis as DR, and | value (DRi) -value (DR) | is greater than 0.3, then the time slice where Wi is located is judged to be the inverted wavelet, the wavelet state SAi is assigned 0001000, otherwise the time slice where Wi is located is judged to be the actual stationary wavelet, and the wavelet state SAi is assigned 0010000. In-period state qualitative analysis SA and SAi are subjected to AND operation, and the values are assigned to SA;
3.3.2 setting the current DRi as the direction DR of the system static state, assigning value (DRi) to value (DR);
the average | AVG (X, Y, Z) | of the three axes XYZ of the 5 sampling points of the 3.3.3 Wi wavelet is a radian value in the XYZ direction, and the radian value is converted into an angle and then compared with the inclination angle extreme values AngleXmax, AngleYmax, AngleZmax of the three axes in the period and updated.
3.4 if the variances of the two wavelets of Wi and Wi +1 in 10 sampling points XYZ three axes are all larger than 0.3, judging that the time slice where Wi is located is an impact wavelet, assigning 0000100 to the state SAi of the wavelet, assigning 0000100 to the value after AND operation is carried out on SA and SAi in the periodic state qualitative analysis, and then finishing the qualitative analysis; otherwise, continuing the next analysis;
3.5 if the variances of 5 sampling points XYZ three axes of the Wi wavelet are all smaller than 0.01, judging that the time slice where the Wi is located is a moving wavelet, assigning 0000010 to the wavelet state SAi, assigning values to SA after performing AND operation on the state qualitative analysis SA and SAi in the period, and then finishing the qualitative analysis; otherwise, continuing the next analysis;
3.6 directly judging that the time slice where Wi is located is a bump wavelet, assigning 0000001 to the wavelet state SAi, and assigning value to SA after performing AND operation on SA and SAi in the state qualitative analysis in the period.
4. And when the period time is up, the following output is made, and after the output, the step 0 is returned to start the analysis of the new period.
4.1 directly outputting extreme values Xmax, Ymax and Zmax of three XYZ axes in the period, inclination angle extreme values AngleXmax, AngleYmax and AngleZmax of the three axes in the period, and state qualitative analysis SA in the period.
4.2 output 0.5 x 9.8 x (FALLmax 0.025), which is the free fall height in meters within the cycle.
Further, the number of the sampling points S (X, Y, Z) is 5, which are formed by reading a plurality of groups of values.
Claims (2)
1. A cargo transportation state detection method comprises a process of fixedly connecting a three-axis acceleration sensor in a cargo or a cargo package and detecting an output signal of the three-axis acceleration sensor by using a microprocessor, and is characterized in that in the process, the microprocessor is used for continuously reading numerical values of the three-axis acceleration sensor in the directions of an X axis, a Y axis and a Z axis at the frequency of 1KHz and carrying out real-time operation;
in the real-time operation process, firstly, initializing system parameters, setting a static state direction DR as an X axis, assigning DR as 1, setting a free FALL height counter FALL value as 0, and setting a theoretical static wavelet counter SN value as 0; after the detection period starts, the extreme values Xmax, Ymax and Zmax of the three axes in the initialization period, the inclination angle extreme values AngleXmax, AngleYmax and AngleZmax of the three axes in the period and the free falling height counter FALLmax in the period are all assigned to be 0, and the qualitative analysis result SA in the period is assigned to be 0000000; continuously reading more than two groups of numerical values, comparing to obtain extreme values of three XYZ axes to form a sampling point S (X, Y, Z), and updating Xmax, Ymax and Zmax if the extreme values of the three axes are greater than Xmax, Ymax and Zmax; after a plurality of groups of sampling points are continuously obtained, every 5 continuous groups of sampling points are selected to form a wavelet W (S1, S2, S3, S4 and S5), so that a plurality of groups of wavelets W are formed, the state of the goods at the moment of the wavelet W can be qualitatively judged by analyzing the three continuous groups of wavelets W, and the qualitative judgment method comprises the following steps:
if the three-axis average values of 5 sampling points of a certain wavelet Wi are all smaller than 0.1, judging that the wavelet Wi is in a free-FALL state, assigning the state qualitative analysis result SAi of the wavelet Wi to be 1000000, adding 1 to the FALL value, updating the FALLmax if the FALL is larger than the FALLmax, giving the SA values after the SA and the SAi are subjected to logic AND operation, and finishing the qualitative analysis of the wavelet Wi; if the triaxial average values of 5 sampling points of a certain wavelet Wi are all larger than or equal to 0.1, the FALL is assigned with 0, and the next analysis is continued;
if the previous wavelet Wi-1 of a certain wavelet Wi is qualitatively analyzed to be in a free falling body state and at least one of the three-axis average values of 5 sampling points of the wavelet Wi is more than 0.1, judging that the wavelet Wi is in a falling collision state, assigning the qualitative analysis result SAi of the state of the wavelet Wi to be 0100000, assigning the value obtained after the SA and the SAi are subjected to logic AND operation to the SA, and completing the qualitative analysis of the wavelet Wi; otherwise, continuing the next analysis;
if the triaxial extreme value differences of 5 sampling points of a certain wavelet Wi are all smaller than 0.15, judging the wavelet Wi to be in a theoretical static state, adding 1 to the SN value, otherwise, assigning the value of a theoretical static wavelet counter SN to be 0, and continuing to analyze in the next step;
if the SN value is greater than 10, the following analysis is carried out; if the axis DRi of the maximum value in the three-axis average values of the 5 sampling points of the wavelet Wi is not the same axis as the DR and the difference between the value of the DRi and the value of the DR is greater than 0.3, judging that the wavelet Wi is in an overturn state, assigning the qualitative analysis result SAi of the state of the wavelet Wi to be 0001000, otherwise, judging that the wavelet Wi is in an actual static state, assigning the qualitative analysis result SAi of the state of the wavelet Wi to be 0010000, assigning the value obtained after the SA and the SAi are subjected to logic AND operation to the SA, updating the static state direction DR to the direction pointed by the DRi, assigning the value of the DRi to the DR, wherein the three-axis average values of the 5 sampling points of the wavelet Wi are arc values in the XYZ direction, converting the arc values into angles, and comparing the angles with the AngleXmax, AngleYmax and AngleZmax and updating the extreme values;
if the condition that the SN value is less than or equal to 10 does not hold or the condition that the triaxial extreme value differences of 5 sampling points of a certain wavelet Wi are less than 0.15 does not hold, continuing the next analysis;
if the variance of three axes of 10 sampling points of a certain wavelet Wi and the next wavelet Wi +1 is larger than 0.3, judging that the wavelet Wi is in an impact state, assigning 0000100 to the qualitative analysis result SAi of the state of the wavelet Wi, and assigning the value obtained after the SA and the SAi are subjected to logic AND operation to the SA; otherwise, continuing the next analysis;
if the three-axis variance of 5 sampling points of a certain wavelet Wi is less than 0.01, judging that the wavelet Wi is in a moving state, assigning 0000010 to the wavelet Wi state qualitative analysis result SAi, and assigning the SA to a value obtained after the SA and the SAi are subjected to logic AND operation; otherwise, continuing the next analysis;
directly judging the wavelet Wi as a bumpy state, assigning 0000001 to the qualitative analysis result SAi of the wavelet Wi state, and assigning the value obtained after the SA and the SAi are subjected to logic AND operation to the SA;
if the cycle time has not ended, continuing to analyze the subsequent wavelets, if the cycle time has ended, outputting the values of the extrema Xmax, Ymax, Zmax of the three axes, the extrema anguxexmax, AngleYmax, AngleZmax of the three axes, and the qualitative analysis result SA of the states in the cycle, and outputting the calculation result of 0.5 x 9.8 (FALLmax 0.025), which is the height of the free fall of the cargo in the cycle.
2. The cargo transport state detection method according to claim 1, wherein the number of the sampling points S (X, Y, Z) constituting the sampling point is 5 groups which are required to continuously read the values.
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| CN111964668B (en) * | 2020-08-12 | 2022-05-10 | 中移（杭州）信息技术有限公司 | Method and device for detecting article state |
| CN112781584A (en) * | 2020-12-25 | 2021-05-11 | 海尔数字科技(无锡)有限公司 | Cargo state detection method based on acceleration sensor |
| CN113793097B (en) * | 2021-09-07 | 2024-04-26 | 珠海格力电器股份有限公司 | Analysis method and system for cargo transportation risk |
| CN113624996B (en) * | 2021-09-07 | 2022-07-12 | 珠海格力电器股份有限公司 | Cargo throwing state identification method and system |
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